Increasing advances in computer technology (e.g., microprocessor speed, memory capacity, data transfer bandwidth, software functionality, and the like) have generally contributed to increased computer application in various industries. Ever more powerful server systems, which are often configured as an array of servers, are often provided to service requests originating from external sources such as the World Wide Web, for example. As local Intranet systems have become more sophisticated thereby requiring servicing of larger network loads and related applications, internal system demands have grown accordingly as well. As such, much business data is stored in databases, under the management of a database management system (DBMS).
For such DBMS systems, a demand for database transaction processing capacity in large installations has been growing significantly. At the same time, a large percentage of overall new database applications have been in a relational database environment. Such relational database can further provide an ideal environment for supporting various forms of queries on the database. For example, a growth in the use of ad hoc unstructured concomitant queries-is a trend that is expected to accelerate in such database environments. This can result in a growing requirement for simultaneously supporting both high volume transaction processing and unstructured queries against the same database. Thus, systems and methodologies that can effectively support both high volume transactions and complex queries, with minimal interference between the two, while sharing copies of data are in demand.
Typically, business entities create and maintain their databases through a high volume of relatively simple transactions, with an essential function of a database engine being able to execute a plurality of such transactions concurrently. Each of such plurality of transactions can be considered a piece of work, which can further consist of a sequence of operations such as, read, write, update, and/or delete, against a database. Such transaction can represent well-understood business operations (e.g., creating a new customer record, noting an account payment or transfer, and the like). Increasingly enterprises are becoming interested in running more ad hoc unstructured queries against their online data. As such, a measure of the correctness of the state of the database or a database integrity becomes increasingly vital.
In general database integrity can refer to the problem of ensuring that two or more concurrently executing transactions do not interfere with each other in such a manner as to produce an incorrect state in the database. An application programmer typically should ensure that each transaction produces a correct state, and that each transaction begins when the database is in a correct state. Such transaction management should generally adhere to the ACID (Atomicity, Consistency, Isolation and Durability) standards. In general, Atomicity can refer to a feature that: either the results of the transaction (i.e., changes to the database) are all properly reflected in the database, or none of them are. When a transaction commits, all changes made to the database by the transaction are durably stored, leaving the database in a consistent state. When a transaction aborts, any changes made to the database by the transaction are backed out, once again leaving the database in a consistent state. Similarly, consistency controls a state of the data should a failure occur. Thus, a transaction must bring the database from one consistent state to another consistent state. Likewise, isolation in general means that the events within a transaction must be hidden from other transactions running concurrently, and that concurrent transactions must not interfere with each other. Put differently, they execute as if they had the database to themselves. Finally, durability typically refers to a feature that once a transaction has been completed and has committed its results to the database, the system must guarantee that these results survive any subsequent malfunctions. Yet, when multiple copies of data pages are created, such standards can be difficult to adhere to. At the same time, the more efficiently a database engine supports concurrent transactions, the better an end-user experience can be in terms of speed of operation and reduced database growth.
Therefore, there is a need to overcome the aforementioned deficiencies associated with conventional systems and methodologies related to database operations.